Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam

Concrete beams and girders; Cost effectiveness; Debonding; Design; Reinforced concrete; Strain; Reinforced concrete beams; Shear reinforcement; Shear strengthening; Strain compatibility; Strengthened beams; Structural investigation; Structural performance; Theoretical design; Shear flow

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Main Authors: Alam M.A., Sami A.
Other Authors: 57199298044
Format: Article
Published: Taylor and Francis Ltd. 2023
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spelling my.uniten.dspace-265772023-05-29T17:12:15Z Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam Alam M.A. Sami A. 57199298044 56443764700 Concrete beams and girders; Cost effectiveness; Debonding; Design; Reinforced concrete; Strain; Reinforced concrete beams; Shear reinforcement; Shear strengthening; Strain compatibility; Strengthened beams; Structural investigation; Structural performance; Theoretical design; Shear flow Optimisation of CFRP shear strip in presence of connectors/anchors is the current interest to reduce retrofitting cost of structures. The main aim of this research was to propose design guideline considering strain compatibility nature between shear reinforcement and externally bonded CFRP laminate to optimise the dimension of CFRP laminate for shear strengthening of RC beam in presence of embedded connectors. The guideline had been experimentally verified through the structural investigations on five reinforced concrete beams. Results showed that the proposed guideline with connectors reduced the dimension of CFRP laminate significantly. The optimal strengthened beams had shown the highest flexural capacities, maximum ductility and cost effective structural performances. Shear reinforcement and externally bonded CFRP laminate had shown identical nature of strains until shear crack and micro debonding of laminate. The optimal strengthened beams with connector did not fail by shear or debonding of laminates prior to theoretical design shear capacities of beams. The design shear capacities of optimal strengthened beams (182 kN) were very close to those of flexural failure loads (181 kN and 184 kN). Overall experimental results satisfactorily verified the proposed design guideline. � 2021 Engineers Australia. Final 2023-05-29T09:12:15Z 2023-05-29T09:12:15Z 2021 Article 10.1080/13287982.2021.1876439 2-s2.0-85101250080 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101250080&doi=10.1080%2f13287982.2021.1876439&partnerID=40&md5=039d02bd0aa3ecc2a2549134ec5432cf https://irepository.uniten.edu.my/handle/123456789/26577 22 1 59 72 Taylor and Francis Ltd. Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description Concrete beams and girders; Cost effectiveness; Debonding; Design; Reinforced concrete; Strain; Reinforced concrete beams; Shear reinforcement; Shear strengthening; Strain compatibility; Strengthened beams; Structural investigation; Structural performance; Theoretical design; Shear flow
author2 57199298044
author_facet 57199298044
Alam M.A.
Sami A.
format Article
author Alam M.A.
Sami A.
spellingShingle Alam M.A.
Sami A.
Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
author_sort Alam M.A.
title Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
title_short Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
title_full Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
title_fullStr Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
title_full_unstemmed Strain compatibility model to optimise CFRP laminate for shear strengthening of RC beam
title_sort strain compatibility model to optimise cfrp laminate for shear strengthening of rc beam
publisher Taylor and Francis Ltd.
publishDate 2023
_version_ 1806426360205279232
score 13.223943